daanelson / speedy-sdxl-test

SDXL, but faster

  • Public
  • 2.5K runs
  • L40S

Input

string
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Input prompt

Default: "An astronaut riding a rainbow unicorn"

string
Shift + Return to add a new line

Input Negative Prompt

Default: ""

integer

Width of output image

Default: 1024

integer

Height of output image

Default: 1024

integer
(minimum: 1, maximum: 4)

Number of images to output.

Default: 1

string

scheduler

Default: "K_EULER"

integer
(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

number
(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 7.5

number
(minimum: 0, maximum: 1)

Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image

Default: 0.8

integer

Random seed. Leave blank to randomize the seed

string

Which refine style to use

Default: "no_refiner"

number
(minimum: 0, maximum: 1)

For expert_ensemble_refiner, the fraction of noise to use

Default: 0.8

integer

For base_image_refiner, the number of steps to refine, defaults to num_inference_steps

boolean

Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.

Default: true

Output

output
Generated in

This example was created by a different version, daanelson/speedy-sdxl-test:f9c99b61.

Run time and cost

This model costs approximately $0.011 to run on Replicate, or 90 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 12 seconds. The predict time for this model varies significantly based on the inputs.

Readme

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